The invention, in some embodiments, relates to the field of retail shopping, and more particularly to methods and devices for improving the shopping experience of a user, both when shopping online and when shopping at a physical retail venue.
In many computerized shopping applications currently available in the market, products can be uniquely identified, for example by identifying the Stock Keeping Unit (SKU) of the product, based on extraction of visual features from the package of the product, typically using computer vision and/or image processing methods. However, in existing products, the database containing all the product images is built manually by an operator. In order to keep the database up to date, each change in the packaging of a product must be manually entered by the operator, which often causes inaccuracies due to update backlog or to the operator being unaware of changes to the packaging.
Various devices and products exist, in which hand movements and object movements are translated into commands, for example using computer vision and/or image processing methods. However, these devices typically require use of a specific object, such as a specific remote control, or may recognize a limited number of objects identified by the user during initial setup.
Many shopping applications existing today include data mining or data analysis technologies designed for product matching, such that they can identify products bought together, or bought by a single user, and make suggestions to other users based on such identification. Additionally, product comparison applications exist, particularly for grocery products, which identify, and offer to the user to purchase, a similar product having a better price, or one which is considered healthier. However, these applications do not take into consideration the specific user's preferences, and therefore often suggest grossly irrelevant products to a user, causing the user to waste time reviewing irrelevant suggestions rather than saving the user's time.
Naturally, all shopping applications receive input from the user as to the desired products. Existing speech recognition algorithms and techniques allow users to vocally input information, and of course also recognize terms relating to groceries and other products for which the user may shop. However, shopping applications existing today do not translate the vocal input recognized by speech recognition mechanisms to identification of a specific product, making it difficult and inefficient to receive the user's input in the form of a vocal command.